Personalized exercise interventions for doctoral students’ mental health: A step beyond one size fits all

Abstract

The global mental health crisis among doctoral students, characterized by a high prevalence of stress, anxiety, depression, and sleep disorders, demands effective, sustainable interventions. By comparing a regimen of “personalized menu-style targeted exercise” with a traditional Tai Chi intervention and found targeted exercise to be more effective in alleviating psychological distress and improving sleep. This review highlights the study’s innovation in developing a symptom-specific, choice-based prescription model, methodological strengths/limitations, and implications for university mental health services. It also guides future research directions toward developing personalized exercise interventions for high-stress academic populations.

Key Words: Personalized exercise; Doctoral students; Mental health; Stress; Sleep disorders; Tai Chi; Intervention efficacy

Core Tip: Some studies demonstrating that personalized, menu-style targeted exercise tailored to symptom profiles (e.g., team sports for depression, resistance training for sleep disorders) outperforms Tai Chi in improving doctoral students’ mental health. By addressing gaps in prior “one-size-fits-all” exercise interventions. This review evaluates methodological strengths and limitations, emphasizing the integration of individual choice with empirical evidence. The review also discusses practical implications for university mental health services and outlines future research directions for precision exercise in psychiatry.

INTRODUCTION

Mental health distress in academia has emerged as a defining public health challenge of the 21^st century, with doctoral students representing one of the most vulnerable subgroups[1-3]. Epidemiological data confirm this disparity: Satinsky et al’s systematic review[4] reported prevalence rates of anxiety and depression of 17% and 24%, respectively, among doctoral candidates, while Anwer et al’s study[5] found that 64% of postgraduate researchers experience sleep disorders - a rate approximately threefold higher than in the general population. This crisis is rooted in unique academic stressors, such as uncertain funding, social isolation, rigorous publication requirements, and ambiguous career prospects. These factors collectively disrupt physiological and psychological homeostasis[6-10].

Traditional interventions for doctoral mental health management have included pharmacological treatments and non-pharmacological approaches like cognitive-behavioral therapy[11-13]. However, these approaches have faced significant barriers, including stigmas around mental health care, time constraints that conflict with research schedules, and financial burdens[14]. Exercise has emerged as a low-cost, low-stigma alternative, with prior studies linking aerobic training[15-17], yoga[18-20], and Tai Chi[21,22] to reduced psychological distress[23,24]. However, a critical limitation of exercise as an intervention is a “one-size-fits-all” approach; most studies have evaluated the effects of single-exercise modalities, while ignoring the heterogeneous needs of doctoral students (e.g., a student with insomnia may benefit more from resistance training than yoga; a student with depression may thrive in team sports but lack motivation in solo exercise).

Against this backdrop, Wu et al’s study[25] fills a crucial gap. By designing a “personalized menu-style targeted exercise” intervention strategy and comparing its effects to the benefits of Tai Chi, the authors not only validated exercise as a viable mental health tool but also redefined how exercise interventions can be tailored to heterogenous academic populations. This review contextualizes Wu et al’s findings[25] within the broader field of academic psychiatry, evaluates their study’s methodological rigor, and maps potential future directions to translate this work into scalable practice.

The study’s core finding is significant: The individually targeted exercise approach was more effective, demonstrating greater durability, alleviating psychological distress, and improving sleep. It challenges the common paradigm in exercise psychiatry that investigates a single, broad-spectrum activity like Tai Chi, yoga, or aerobic exercise in isolation. While each of these practices have undeniable benefits, Wu et al[25] compellingly argue that a monolithic approach does not optimally serve a heterogeneous high-stress group like doctoral students, who have diverse physiological and psychological needs, preferences, and biological rhythms.

INNOVATION: THE PERSONALIZED PRESCRIPTION MODEL

The core innovation of Wu et al’s study[25] is not the introduction of new exercise forms, but its paradigm shifts from a “one-size-fits-all” approach to precision exercise prescription, an idea that is consistent with the broader objectives of precision psychiatry. Unlike previous mental health exercise intervention studies, which primarily focused on isolating single modalities[16,24] with little consideration for individual differences in symptom profiles, preferences, or biological responses, Wu et al[25] novel intervention approach addresses this gap through symptom-specific targeting. Each exercise modality is explicitly linked to a distinct mental health outcome based on plausible mechanisms (Table 1). Baduanjin reduces anxiety by regulating the autonomic nervous system[26], team sports alleviate depression by tackling social isolation via increased cohesion and mutual support[27-29], and resistance training improves sleep by inducing moderate muscle fatigue and boosting self-efficacy[30-33]. The study further validated symptom-exercise alignment with Bayesian correlation data, which showed that each modality correlated strongly with its intended outcome (e.g., yoga with the Insomnia Severity Index and team sports with the Patient Health Questionnaire-9).

Table 1 Symptom-specific exercise modalities, mechanisms and assessment scales for doctoral students.

Mental health symptom	Targeted exercise	Core mechanism	Assessment scale
Anxiety	Baduanjin, ball sports, swimming	Regulates autonomic nervous system; soothing auditory/rhythmic stimulation	Generalized Anxiety Disorder 7-item scale
Depression	Team sports, group yoga	Alleviates social isolation; enhances social cohesion	Patient Health Questionnaire-9
Stress	Morning jogging, Baduanjin	Balances HPA axis; relieves acute stress	Perceived Stress Scale-10
Daytime sleepiness	Morning jogging	Regulates circadian rhythm; improves daytime alertness	Epworth Sleepiness Scale
Insomnia	Resistance training, yoga	Induces muscle fatigue; relaxes muscles/regulates breathing	Insomnia Severity Index
Poor sleep quality	Resistance training, yoga	Improves sleep architecture; promotes physical relaxation	Pittsburgh Sleep Quality Index

HPA: Hypothalamic-pituitary-adrenal.

The second key design feature of Wu et al[25] intervention - individual choice and improved adherence - was achieved through a “menu-style” format that allowed students to select exercise modalities matching their preferences and schedules. This flexibility directly addressed doctoral students’ common challenges, such as time constraints and fluctuating energy levels. By combining symptom specificity and individual choice, the model shifts the field’s focus from the binary question “Does exercise work for improving mental health?” to the more clinically relevant “Which exercise works best for which individual, for which symptom, and under what circumstances?” This is a crucial step in advancing evidence-based exercise prescription in psychiatry.

METHODOLOGICAL STRENGTHS AND LIMITATIONS

Wu et al’s study[25] offers valuable preliminary evidence for personalized menu-style targeted exercise, with notable methodological strengths. Strict inclusion/exclusion criteria minimized heterogeneity, while well-matched baseline characteristics (demographic, clinical, and psychological indicators, all P > 0.05) reduced selection bias. Validated Chinese versions of core scales (e.g., the Epworth Sleepiness Scale[34-36], Pittsburgh Sleep Quality Index[37-39], Generalized Anxiety Disorder 7-item scale[40-42]) ensured reliable symptom measurement, and five rounds of Delphi assessments[43-45] by 24 interdisciplinary experts confirmed intervention feasibility (Kendall’s W = 0.859, P < 0.001).

However, critical limitations require in-depth scrutiny. First, the retrospective design overlooked unmeasured confounders - including prior exercise history, social support variability, and academic stress stratification - that may have modulated the causal link between personalized exercise and mental health improvements. Second, the attenuated 12-week follow-up effects cannot simply be reduced to “lack of persistence”; potential drivers include fixed intervention dosage (without progressive overload) and failure to adapt modalities to evolving symptoms, alongside discontinued supportive post-intervention structures. Third, mechanistic exploration was fragmented: The study lacked a comparative analysis of distinct pathways (e.g., resistance training vs yoga for sleep), ignored “physiological-psychological-social” synergies, and overlooked individual difference roots (gender, genetics, chronotype) that shape exercise responses. These limitations constrain causal inference, sustainability insights, and mechanistic clarity, highlighting the need for future research to address these gaps.

PRACTICAL IMPLICATIONS FOR ACADEMIA AND CLINICAL PRACTICE

Wu et al’s study[25] has direct, scalable implications for university mental health services and clinical practice seeking to address doctoral students’ wellness needs, with key actionable strategies that focus on intervention design and accessibility. First, universities should replace or supplement single-modality exercise programs with “mental well-being exercise menus” that pair specific exercise modalities with targeted symptoms: Ball games or swimming for anxiety (leveraging rhythmic movements and soothing auditory stimuli), team sports or group yoga for depression (fostering social connection to counter isolation), and resistance training or evening yoga for insomnia (targeting muscle relaxation and circadian regulation). These menus should be integrated into student health portals, accompanied by clear guidelines and a brief online screener using the Generalized Anxiety Disorder 7-item scale and Patient Health Questionnaire-9[46-48], to help students select appropriate modalities based on their symptom profiles. Second, to maximize adherence, programs must prioritize flexibility in scheduling and location, while peer support systems like “exercise buddies” or student-led teams can further boost participation.

Beyond initial intervention design, the study also highlights the need for long-term sustainability and clinical integration. Given the observed attenuation of effects at the 12-week follow-up, universities should prioritize long-term exercise habit formation through progressive programs, ongoing reminders, and promoting exercise as contributing to academic success (e.g., linking participation to wellness credits). For doctoral students with moderate-to-severe mental health symptoms, exercise interventions should be integrated with clinical care (e.g., cognitive-behavioral therapy or pharmacotherapy) as an adjunctive treatment. Wu et al’s findings[25] suggest this integration can enhance the efficacy of traditional clinical approaches, reducing reliance on medications and their potential side effects.

FUTURE RESEARCH DIRECTIONS

To advance precision exercise interventions for doctoral students’ mental health, future research must first address the limitations of Wu et al’s study[25] while refining its foundational research designs and outcome assessments. A key priority is conducting large-scale, multicenter prospective randomized controlled trials with diverse samples, spanning regions, academic disciplines, and demographics to establish causality and improve generalizability. These trials should include a waitlist control group to isolate intervention effects and 6-12 months of long-term follow-up to evaluate sustained benefits. Additionally, integrating objective biomarkers into outcome assessments is critical for validating self-reported symptoms. For example, stress can be assessed through short-term salivary[49,50]/plasma[51,52] cortisol levels and long-term hair[53,54] cortisol levels[55]; sleep can be evaluated using actigraphy (for duration and efficiency) or polysomnography (for sleep architecture)[56]; and anxiety and depression can be validated via functional magnetic resonance imaging of the amygdala and prefrontal cortex to assess neural correlates of symptom reduction[57-61]. Future studies should use factorial designs to disentangle the independent and interactive effects of key intervention components, such as symptom targeting (e.g., resistance training for insomnia vs anxiety), individual choice (e.g., menu-style options vs assigned exercises), and exercise variety (e.g., multi-modality vs single-modality approaches). This strategy would help identify the most cost-effective and efficient elements of the interventions. Finally, exploring subgroup differences - such as by doctoral stage (e.g., first-year adjustment stress vs final-year thesis stress), by sex (e.g., variations in exercise preferences and symptom responses); and by discipline (e.g., the stress of long lab hours in STEM fields vs the stress of writing in humanities) - will enable the development of more tailored interventions.

Beyond refining design and assessment, future research should embrace technological innovation and deepen mechanistic understanding. Developing digital platforms, such as mobile apps integrated with machine learning algorithms, can personalize exercise prescriptions based on baseline symptom profiles, real-time data (e.g., actigraphy and self-reported mood), and adherence patterns. These platforms could dynamically adapt interventions - such as increasing team sports if depression worsens or switching to resistance training if sleep quality declines. Equally important are mechanistic studies to elucidate how targeted exercise improves mental health, such as determining whether Baduanjin reduces anxiety by modulating vagal nerve activity or if resistance training enhances sleep by modulating the hypothalamic-pituitary-adrenal axis[26,56]. Such insights will inform the development of more potent, evidence-based interventions rooted in biological and psychological mechanisms, rather than relying solely on observational associations.

CONCLUSION

Wu et al[25] have successfully shifted the conversation in the field of exercise and mental health. Their work provides preliminary but compelling evidence that the future of exercise interventions for high-stress populations may lie in personalization and choice. By moving beyond a single-modality approach, we can develop more precise, engaging, and effective strategies to support the psychological well-being of those navigating the immense challenges of doctoral education. This study is not the final word, but a vital and welcome catalyst for a more nuanced, person-centered, and effective approach to mental health promotion in academia and beyond.